detect_outliers

jwst.outlier_detection.ifu.detect_outliers(input_models, save_intermediate_results, kernel_size, ifu_second_check, threshold_percent, make_output_path)[source]

Flag outliers in IFU data.

Parameters:
input_modelsModelContainer

A container of data models or an association file readable into a ModelContainer.

save_intermediate_resultsbool

If True, save intermediate results.

kernel_sizestr

The size of the kernel to use to normalize the pixel differences. Must only contain odd values. Valid values are a pair of ints in a single string (for example ‘7 7’, the step default).

ifu_second_checkbool

If True, perform a secondary check for outliers. This will set outliers wherever the difference array of adjacent pixels is a NaN.

threshold_percentfloat

The threshold (in percent) of the normalized minimum pixel difference used to identify bad pixels. Pixels with a normalized minimum difference above this percentage are flagged as outliers.

Returns:
input_modelsModelContainer

The input data with DQ flags set for detected outliers.